Sign up to receive free email alerts when patent applications with chosen keywords are publishedSIGN UP

Abstract:

Systems, method, and media for providing advertisements based upon
relational data are provided herein. According to some embodiments,
method for processing queries may include the steps of receiving query
via a web server, from a client device, generating, via the web server, a
response for the query by determining a header object in the query,
determining connected entities in a database for the header object, and
assembling the connected entities together into the response according to
a long-tail response format.

Claims:

1. A method for processing a query, the method comprising: receiving
query via a web server, from a client device; generating, via the web
server, a response for the query by: determining a header object in the
query; determining connected entities in a database for the header
object; and assembling the connected entities together into the response
according to a long-tail response format; and returning the response to
the client device.

2. The method according to claim 1, wherein the long-tail response format
begins with the header object, wherein each subsequent connected entity
is relationally connected with an immediately preceding connected entity.

3. The method according to claim 1, wherein at least one of the connected
entities comprises an advertisement.

4. The method according to claim 1, wherein at least one of the header
object and the connected entities comprises a current advertisement and
at least one of the header object and the connected entities comprises a
legacy advertisement.

5. The method according to claim 1, wherein the response comprises an
image file for the header object and each of the connected entities,
wherein the image files are assembled together according to the long-tail
response format.

6. The method according to claim 1, further comprising returning a
product suggestion that corresponds to at least one of the connected
entities in the response.

7. The method according to claim 6, wherein the product suggestion has a
different domain type than the domain type of the header object.

8. A method for providing advertisements based upon relational data, the
method comprising: receiving query via a web server, from a client
device; generating, via the web server, a response for the query by:
determining a header object in the query; locating a first advertisement
associated with the header object; and locating a legacy advertisement if
the first advertisement is a current advertisement or a current
advertisement if the first advertisement is a legacy advertisement; and
returning the response to the client device.

9. The method according to claim 8, further comprising returning the
first advertisement and the legacy or the current advertisement in a
timeline format.

10. The method according to claim 9, wherein the timeline format begins
with the first advertisement, wherein the legacy advertisement or the
current advertisement are linked with the first advertisement according
to an advertisement age.

11. A system for processing a query, the system comprising: at least one
server that is selectively coupleable to a client device, the at least
one server comprising a processor configured to execute instructions that
comprise: a query module that receives query from a client device; and an
analysis module that generates a response for the query by: determining a
header object in the query; determining connected entities in a database
for the header object; assembling the connected entities together into
the response according to a long-tail response format; and returning the
response to the client device.

12. The system according to claim 11, wherein the long-tail response
format begins with the header object, wherein each subsequent connected
entity is relationally connected with an immediately preceding connected
entity.

13. The system according to claim 11, wherein at least one of the
connected entities comprises an advertisement located by an advertisement
module.

14. The system according to claim 11, wherein at least one of the header
object and the connected entities comprises a current advertisement and
at least one of the header object and the connected entities comprises a
legacy advertisement.

15. The system according to claim 11, wherein the response comprises an
image file for the header object and each of the connected entities,
wherein the image files are assembled together according to the long-tail
response format.

16. The system according to claim 11, further comprising an advertisement
module that returns a product suggestion to the client device that
corresponds to at least one of the connected entities in the response.

17. The system according to claim 16, wherein the product suggestion has
a different domain type than the domain type of the header object.

18. The system according to claim 11, further comprising an advertisement
module that: locates a first advertisement associated with the header
object; and locates a legacy advertisement if the first advertisement is
a current advertisement or a current advertisement if the first
advertisement is a legacy advertisement.

19. The system according to claim 18, wherein the advertisement module
returns the first advertisement and the legacy or the current
advertisement in a timeline format.

Description:

CROSS REFERENCE TO RELATED APPLICATION

[0001] This Non-Provisional U.S. Patent Application claims priority to
Provisional U.S. Patent Application 61/505,113, filed on Jul. 7, 2011,
entitled "SYSTEMS, METHODS, AND MEDIA FOR PROVIDING ADVERTISEMENTS BASED
UPON RELATIONAL DATA" which is hereby incorporated by reference herein in
its entirety.

FIELD OF THE INVENTION

[0002] This invention relates generally to providing of advertisements,
and more particularly, but not by way of limitation, to systems, methods,
and media that provide advertisements based upon relational data.

BACKGROUND

[0003] The provision of advertisements is well known in within the online
media arts. While the provision of advertisements is well known, the
systems and methods that provide these advertisements often utilize
randomized advertising. Additionally, while the personalization of
advertisements may alleviate some of the drawbacks of randomized
advertising schemas, static advertising content (even when personalized)
may become stagnant and ineffective.

[0004] Additionally, while advertisements may be personalized, such
personalized advertisements depend upon data that directly correlates the
advertisement to the customer. For example, if the advertiser knows that
the customer enjoys a particular artist, the advertiser may provide
specific advertisements that are associated with product or services
offered by the artist.

[0005] Unfortunately, these types of direct correlation advertisements
cannot suggest valuable, yet non-intuitive products or services to the
customer. Similarly, none of these systems or methods provide current
advertisements based upon the presentation of legacy advertisements, nor
do they facilitate the use of dynamically presented advertising schemas
that selectively rotate advertisements to substantially reduce end user
advertising fatigue.

SUMMARY OF THE INVENTION

[0006] According to some embodiments, the present technology may be
directed to methods for processing a query that comprises the steps of:
(a) receiving query via a web server, from a client device; (b)
generating, via the web server, a response for the query by: (i)
determining a header object in the query; (ii) determining connected
entities in a database for the header object; and (iii) assembling the
connected entities together into the response according to a long-tail
response format; and (c) returning the response to the client device.

[0007] According to additional embodiments, the present technology may be
directed to methods providing advertisements based upon relational data
that comprises the steps of: (a) receiving query via a web server, from a
client device; (b) generating, via the web server, a response for the
query by: (i) determining a header object in the query; (ii) locating a
first advertisement associated with the header object; and (iii) locating
a legacy advertisement if the first advertisement is a current
advertisement or a current advertisement if the first advertisement is a
legacy advertisement; and (c) returning the response to the client
device.

[0008] According to exemplary embodiments, the present technology may be
directed to a system for processing a query that comprises: (a) at least
one server that is selectively coupleable to a client device, the at
least one server comprising a processor configured to execute
instructions that comprise: (i) a query module that receives query from a
client device; and (ii) an analysis module that generates a response for
the query by: (1) determining a header object in the query; (2)
determining connected entities in a database for the header object;
assembling the connected entities together into the response according to
a long-tail response format; and (3) returning the response to the client
device.

BRIEF DESCRIPTION OF THE DRAWINGS

[0009] FIG. 1 is an architectural diagram of an exemplary system for
practicing the present technology.

[0010] FIG. 2 is an exemplary relational analysis system, constructed in
accordance with the present technology.

[0011]FIG. 3 is a flowchart of an exemplary method for providing a
current advertisement based upon the provision of a legacy advertisement.

[0012]FIG. 4A is a flowchart of an exemplary method for providing
advertisements based upon relational data.

[0013] FIG. 4B is flowchart of another exemplary method for providing
selective advertisements based upon relational data

[0014]FIG. 5 is an architectural diagram of an exemplary computing system
for practicing the present technology.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

[0015] According to some embodiments, the present technology may be
directed to the provision of advertisements based upon relational data.
In other embodiments, the present technology may be directed to the
provision of current advertisements based upon the provision of a legacy
advertisement (or vice versa), thereby enhancing the generation of
advertising revenue by legacy advertisements. In some applications, the
legacy advertisements may be displayed within the context of a graphical
display of relational data.

[0016] It will be understood that "legacy advertisements" may include
advertisements that are no longer being actively or currently utilized by
the advertising entity (e.g., marketers, company, etc.). These legacy
advertisements may include any of videos, audio, images, documents, and
combinations thereof, along with any other types of advertisements that
would be known to one of ordinary skill in the art with the present
disclosure before them. These types of legacy advertisements are often
older and less relevant to the advertiser than current advertisements.
For example, a legacy advertisement may include an endorsement from an
artist who is not longer relevant. While legacy advertisements may be
older and/or less relevant to the advertiser, these legacy advertisements
may be of interests to customers or other viewers who are interested in
brand development, brand evolution, or brand nostalgia--just to name a
few.

[0017] In contrast, "current advertisements" may include advertisements
that correspond to active advertising campaigns, and may correspond to
products or services that are currently being offered to consumers or
other similar advertising targets.

[0018] The present technology may utilize relational analyses of objects
as a basis for providing advertisements. It will be understood that a
relationship between a first object and one or more additional objects
(e.g., connected entities) may be based upon one or more relatable
characteristics, relationships, or connections shared therebetween. For
example, the relationships between a musician and their discography,
influences, etc., could relate the musician to other musicians, books,
movies, and the like.

[0019] In addition, the present technology may be configured to correlate
similar or different types of objects together based upon one or more
relatable characteristics or relationships shared therebetween. The
present technology may then trace a path(s) between the two or more
objects and explain the relationships therebetween. For example, a
musician may be indirectly related to a particular product based upon any
one or more of a number of factors (e.g., a know relationship, explicit
statements, and so forth). The systems provided herein may visually
depict both the musician and the author utilizing image files, along with
any intervening objects that connect the two objects together. Data that
was utilized to connect the two objects together may also be provided to
enhance the presentation of data to the end user. In other embodiments,
the present technology may utilize a ribbon of images for each
intervening object. These intervening images may be positioned between
the images of the two objects to create a visual, diagrammatic path
therebetween.

[0020] The present technology may then search the relational database(s)
using the information for the object. The present technology may
determine one or more additional objects within the relational database
that are relevant or correlated to a first object. Objects may be either
directly connected (e.g., only one connection away) or indirectly
connected (e.g., greater than one connection away) together. Exemplary
direct connections may include a musician and their discography.

[0021] It will be understood that a correlation or relationship between
two or more objects may be determined from knowledge or information
gathered regarding objects. Therefore, the greater the amount of
information known about an object, the greater likelihood that a
correlation (or multiple correlations) to another object may be
determined. The types of knowledge or information regarding an object may
include any type of descriptive information about the object. Information
may be input into the system by scraping web content (e.g., web pages,
crawling or searching third party databases, direct input from system
administrators, or may even include information gathered via
crowdsourcing where end users may contribute information or knowledge
about objects).

[0022] To establish connections between objects in response to a query,
the present technology may crawl a relational database to create a graph
of objects and connections out to a defined radius around a first object.
Advantageously, the present technology may gather these additional
objects and sort them based on the rank of each object. For example, if
the first object is connected to an additional object via numerous
connections, the additional object may be ranked higher than other
objects having fewer connections therebetween.

[0023] This collection of objects is then presented to the user in a
visually apprehensible format, such as a graphical user interface that
includes one or more graphs created from depictions of the objects.

[0024] According to some embodiments, the present technology may be
configured to perform a method for correlating objects together in a
database according to relational data. The present technology may be
configured to, for each object in a database, determine a static weight,
the static weight representing a number of relational connections between
each object and one or more connected entities. Additionally, the present
technology may be adapted to set a delta weight for each object, the
delta weight being equal to the static weight.

[0025] In some instances, the present technology may determine which
object in the database comprises a highest delta weight, and also
propagate the highest delta weight of the object to each of the connected
entities. In accordance with the present disclosure, the analysis module
may add the highest delta weight to a static weight and a delta weight
for each of the connected entities and set the delta weight for the
object to zero.

[0026] It is noteworthy to mention that the method executed by the present
technology may terminate the method upon determining that a highest delta
weight for at least one object is below a threshold value.

[0027] According to some embodiments, the present technology may determine
a relevancy for a direct or indirect connected entity based upon any of a
static weight, distance, connection type, or any combinations thereof.

[0028] With regard to weighting, each object may be provided with at least
one of a static weight and a dynamic weight. The present technology may
associate a static weight with an object that includes a defined weight
for each different connection type (e.g., connected entities associated
with the object). According to some embodiments, each object starts with
an initial static weight Wi, and delta weight dWi. In some instances, the
static weight and the delta weight are substantially equal in magnitude
to one another. Initially, the Wi and dWi of an object may be a non-zero
value. The dWi value may be based on an amount and/or connection weight
for each of the connected entities and other similar data.

[0029] In operation, the present technology may be configured to find a
first object i that has largest dWi. The present technology may, for a
first object, "shoot" or propagate a dWi to each connected entity j
(e.g., additional objects that are directly connected to the object i).
The present technology determines connected entities j by searching the
relational database for directly connected objects. Thus, the present
technology may iteratively locate an object in the database with the
highest delta weight value and propagate the delta weight to each of the
object's directly connected entities. Thus, after propagating the delta
weight for an object having the highest delta weight in the database, the
present technology may repeat the process by subsequently locating an
additional object in the database with the highest delta weight. After
dWi is applied to each connected object j, the present technology may set
the dWi to zero. Again, it is noteworthy to mention that this process may
be repeated for every object i in the graph (or database if the graph or
matrix has not been created).

[0030] In some embodiments, the dWi for an object may be scaled by a
connection rank for a connection between the object i and object j. This
value may be referred to as the dWij. The dWij may be added to both the
dWj and the Wj of a connected entity j such that the sum of Wj and dWij
equal the Wj. Moreover, the sum of the dWj and the dWij may equal dWj.

[0031] According to some embodiments, the present technology may be
configured to propagate the rank of each object i through the entire
graph. For example, the present technology may iteratively propagate the
rank of each object i to its direct or adjacent neighbors. It will be
understood that the present technology may propagate the ranks of objects
periodically or continually to allow for full propagation throughout the
relational database.

[0032] Additional details regarding the processes for conducting
relational analyses are described in greater detail with regard to U.S.
Provisional patent application Ser. No. 13/544,980, filed on Jul. 9,
2012, entitled "SYSTEMS, METHODS, AND MEDIA FOR CORRELATING OBJECTS
ACCORDING TO RELATIONSHIPS," which is hereby incorporated by reference
herein in its entirety including all references cited therein.

[0033] FIG. 1 illustrates an exemplary architecture 100 for practicing
aspects of the present technology. Architecture 100 is shown as generally
having a client device 105 that is communicatively couplable with a
relational marketing system 110, hereinafter "system 110." It will be
understood that a plurality of client devices may communicatively couple
with the system 110 via a private or public communications network such
as the Internet.

[0034] Generally speaking, the system 110 may include one or more web
servers 115a-n and one or more relational databases, such as relational
database 120. The servers 115a-n may each be generally described with
reference to computing system 500, described in greater detail with
reference to FIG. 5, although it will be understood that one or more of
the servers 115a-n may include a particular purposes computing system
configured to provide advertisements based upon relational data.

[0035] The system 110 may communicatively couple with a variety of third
party content repositories 125. These content repositories 125 provide
the system 110 with digital content that corresponds to correlated
objects. Digital content may include textual content, images, audio
files, and video files--just to name a few. For example, when exploring
the relationships between a musician and their influences, image files
for both the musician and their influences may be obtained by the system
110 from one or more content repositories.

[0036] Additionally, theses third party content repositories 125 may store
and maintain advertisements that are provided to the system 110 upon
request. Advertisements may include any interactive or non-interactive
media such as web pages, banner advertisements, videos, hypervideos,
audio, image files, and so forth. The system 110 may also be configured
to combine a plurality of individual advertisements together to form a
dynamic advertising campaign, as will be discussed in greater detail
infra. In other embodiments, the system 110 may provide one or more
current advertisements based upon the presentation of one or more legacy
advertisements. In yet other embodiments, the system 110 may be
configured to provide suggestive advertising based upon relation data
linking one or more objects together.

[0037] According to some embodiments, the system 110 may communicatively
couple with the third party content repositories 125 via an application
programming interface ("API"). The API may utilize either secured or
unsecured communications protocols for the transmission of data between
the system 110 and the third party content repositories 125.

[0038] One of ordinary skill in the art will appreciate that the
architecture 100 may include many other devices or systems (e.g.,
routers, firewalls, load balancers, and so forth) that allow for a
plurality of client devices to interact with the system 110 or a
plurality of content provider systems. A detailed discussion of these
additional devices or systems has been omitted for the purpose of
brevity.

[0039] In some embodiments, the system 110 may be configured a cloud
computing environment. In general, a cloud-based computing environment is
a resource that typically combines the computational power of a large
grouping of processors (such as within servers 115a-n) and/or that
combines the storage capacity of a large grouping of computer memories or
storage devices (such as relational database 120). For example, systems
that provide a cloud resource may be utilized exclusively by their
owners, such as Google® or Yahoo!®; or such systems may be
accessible to outside users who deploy applications within the computing
infrastructure to obtain the benefit of large computational or storage
resources.

[0040] The cloud may be formed, for example, by a network of web servers
such as web servers 115a-n with each server (or at least a plurality
thereof) providing processor and/or storage resources. These servers may
manage workloads provided by multiple users (e.g., cloud resource
customers or other users). Typically, each user places workload demands
upon the cloud that vary in real-time, sometimes dramatically. The nature
and extent of these variations typically depends on the type of business
associated with the user.

[0041] According to some embodiments, the system 110 may facilitate the
use of a website or web-based interface that is accessible by the client
device 105. Utilizing the website, end users may graphs associated with
relation analyses, query for objects such as prospective purchases, view
suggestive advertisements that correspond to the query--just to name a
few. In other embodiments, the system 110 may be accessed via an
executable application that resides on the client device 105, or within a
cloud based computing environment.

[0042] FIG. 2 illustrates an exemplary relational marketing system 200
that may reside with the system 110. The relational marketing system 200
may be generally described as being configured to provide advertisements
based upon relational data such as connections between two or more
objects.

[0043] Suggestive Advertisements

[0044] According to some embodiments, the relational marketing system 200
may provide creative or non-intuitive suggestive advertisements based
upon data gathered from a query. For example, if an individual desires to
purchase a creative or thoughtful product or service for a target
consumer, the individual may query the relational marketing system 200
for products that are associated with one or more known interests of the
target consumer. The individual may input any type of data such as a name
of a favorite artist or a title of a film into a query.

[0045] As will be discussed below, because the relational marketing system
200 may utilize a long-tail response format that connects seemingly
unrelated objects in a database, the relational marketing system 200 may
be adept at providing non-intuitive product suggestions. In some
instances, the header object may have a first domain type, such as a
musician, while a second object (e.g., a connected entity) may have a
different domain type, such as a book. For example, if the end user
inputs the name of a musician, the relational marketing system 200 may
create a long-tail format response that includes albums from the
musician, as well as a book that inspired the musician for one of these
selected albums. Each of the albums and the books would be a connected
entity to the musician. Using the domain type differential, the
relational marketing system 200 may select the book as a product
suggestion. The relational marketing system 200 may obtain an
advertisement or a link to the book that is then provided to the end user
as a non-intuitive product suggestion. That is, a product suggestion may
in some instances be an advertisement for a particular product and/or
service.

[0046] The relational marketing system 200 may utilize indirect
connections discovered via relational analysis that link the objects of
the query (e.g., favorite artist) and other objects such as books, music,
locations of interest, and so forth. Based upon known indirect (or even
direct) connections, the relational marketing system 200 may select data
that corresponds to each of the indirect connections such as images,
album covers, audio files, and the like.

[0047] The relational marketing system 200 may arrange these objects into
a graph or matrix and publish the graph to the web based interface or
other display mechanism.

[0048] Upon selection of one or more of the indirectly correlated objects,
the relational marketing system 200 may display the intermediate objects
between the first object (object of the query) and the end point object
(an object having an indirect connection). Because the relational
marketing system 200 may provide visual depictions of intermediate
objects, individuals may visually apprehend the relationship between the
two objects. For example, an album by a particular band (first object)
may be related to a film (indirectly related object) based upon the fact
that a member of the band is related to the lead actor of the film.

[0049] It will be understood that the analysis module 210 may analyze
multiple query objects and determine suggestive advertisements based upon
weighting or ranking of connections between objects. For example, if the
query includes a favorite musician and a favorite vacation destination,
the analysis module 210 may provide suggestive advertising that includes
ticket price data for a concert for the musician that is to occur at the
vacation destination.

[0050] The analysis module 210 may process any number of objects and weigh
the connections therebetween. As such, the analysis module 210 may not
present suggestive advertisements for objects that have fewer connections
to the first object. For example, the analysis module 210 may determine
that a particular band local based in the vacation destination was
influenced by the favorite musician. While the analysis module 210 may
determine that these connections exist, the analysis module 210 may be
configured to weight the "influenced by" connection less than a more
direct connection of the vacation destination itself. Stated otherwise,
the connection may be too indirectly related to the first object.

[0051] Objects having connections with relatively greater weight (e.g.,
numerous connections) relative to the other objects may be considered by
the analysis module 210 to be more relevant with regard to the provision
of suggestive advertising.

[0052] According to additional embodiments of the present technology,
suggestive advertisements may be displayed via a web based graphical user
interface generated by the advertising module 210. In some embodiments,
the display of suggestive advertisements may include, but is not limited
to, an image file of the product or service along with a hyperlink to the
product or service provider's domain or contact data. In other
embodiments, the system 200 may facilitate transactions concerning the
products or services by allowing individuals to purchase the products or
services that correspond to the suggestive advertisements by way of an
e-commerce transaction facilitated by the system 200.

[0053] In some applications, the relational marketing system 200 may also
provide a summary or narrative of the connections between the two objects
such that the individual is provided with an explanation of how the two
objects correspond to one another. Therefore, the relational marketing
system 200 may provide individuals with a non-intuitive/thoughtful
product or service that is highly relevant to the preferences of the
target consumer.

[0054] According to some embodiments, the relational marketing system 200
may generally be described as including a query module 205, an analysis
module 210, and an advertisement module 215. It is noteworthy that the
relational marketing system 200 may include additional modules, engines,
or components, and still fall within the scope of the present technology.
As used herein, the term "module" may also refer to any of an
application-specific integrated circuit ("ASIC"), an electronic circuit,
a processor (shared, dedicated, or group) that executes one or more
software or firmware programs, a combinational logic circuit, and/or
other suitable components that provide the described functionality. In
other embodiments, individual modules of the relational marketing system
200 may include separately configured web servers.

[0055] The query module 205 may receive queries for suggestive
advertising. In some applications, the query module 205 may receive
queries from a web interface that couples the client device 105 to the
relational marketing system 200. Upon receipt of a query, the query
module 205 may parse the query to determine objects included in the
query. For example, the query module 205 may determine names, dates,
locations, and the like, from a received query. The query module 205 may
also utilize machine learning algorithms to improve efficiency and
accuracy of system. For example, the query module 205 may utilize machine
learning to determine that a query including the words "New" and "York"
should be combined into "New York" rather than being understood by the
system to be separate and unrelated words.

[0056] Each received query may be managed as a separate event and logged
for further analysis. Moreover, web analytics may be gathered from the
client device 105 each time a query is received therefrom.

[0057] The query module 205 may communicatively couple with the analysis
module 210. That is, the query module 205 may communicate data that
corresponds to objects that have been determined from a received query.
For example, the query module 205 may communicate the string "David
Bowie" to the analysis module 210, based upon receiving a query that
includes the term "David Bowie."

[0058] The analysis module 210 may then search the relational database 120
using the data for the object. The analysis module 210 may determine one
or more additional objects within the relational database 120 that are
relevant or correlated to a first object. As stated previously, objects
may be either directly connected (e.g., only one connection away) or
indirectly connected (e.g., greater than one connection away) together.
Exemplary direct connections may include a musician and individual albums
within their discography.

[0059] It will be understood that a correlation or relationship between
two or more objects may be determined from knowledge or data gathered
regarding objects. Therefore, the greater the amount of data known about
an object, the greater likelihood that a correlation (or multiple
correlations) to another object may be determined. The types of knowledge
or data regarding an object may include any type of descriptive data
about the object. Data may be input into the system by scraping web
content (e.g., web pages, crawling or searching third party databases,
direct input from system administrators, or may even include data
gathered via crowdsourcing where end users may contribute data or
knowledge about objects.

[0060] Utilizing known connections that are stored within the relational
database 120, the analysis module 210 may cooperate with the advertising
module 215 to obtain suggestive advertising. The analysis module 210 may
obtain advertising from one or more of third party content repositories
125. These advertisements may be downloaded or streamed by the system 200
directly from one or more of the repositories.

[0061] According to some embodiments, the present technology may be
directed to the generation of long-tail responses to queries. That is,
rather than returning a single response to a query that includes a single
object or multiple objects that are themselves unrelated to one another,
the present technology may be configured to generate long-tail responses
for queries. Thus, when generating a query response, the present
technology begins with a header object, which is the object included
in/determined from the query. To complete the response, additional
objects are "attached" to the header object such that each successive
object that is added to the response is related to the object which
precedes it. Stated otherwise, each connected entity (except for the
header object) is relationally connected with an immediately preceding
connected entity Therefore, the response creates a "tail" of related
objects that extend from the header object. The linkages that join the
objects of the tail together are the known relationship values, which
have been described in greater detail above.

[0062] These long-tail query responses may be utilized to create a
long-tail response that includes a plurality of current and legacy
advertisements relative to a header object. For example, if a query
comprises a request for a particular artist, the analysis module 210 may
set the artist as the header object. The advertising module 215 may
search various databases for current and/or legacy advertisements that
are related to the header object (e.g., the artist). For example, the
artist may have endorsed a particular product in a legacy radio jingle
for the product. The advertising module 215 may search databases for
additional advertisements for that same product (either current or
legacy).

[0063] In an additional exemplary embodiment, an end user may query for a
product. Using the name of the product as the header object, the
advertising module 215 may search various databases for current and/or
legacy advertisements associated with the product. Using advertisement
age as a linkage, the advertising module 215 may join the advertisements
together in a long-tail format to assemble the advertisements into a
timeline of advertisements. The timeline may be displayed to the end user
such that clicking any of the advertisements on the timeline causes the
advertisement to be displayed to the end user.

[0064] Legacy/Current Advertisements

[0065] The advertising module 215 may obtain advertisements by searching
the third party content repositories 125 for data, metadata, tags, or
other indicative data that links an object to an advertisement. For
example, a musician may be connected to a video advertisement for a
product because the musician was featured in the video advertisement. As
such the video advertisement may be tagged with the name of the musician
for ease in searching and retrieval via search query. Interrelating
advertisements to subject matter would be well within the knowledge of
one of ordinary skill in the art. Therefore, a detailed discussion of
these methods or processes has been omitted for the purposes of brevity.

[0066] It will be understood that if the video advertisement includes a
legacy advertisement, the advertising module 215 may obtain one or more
current advertisements that are to be presented along with the legacy
advertisement. The current advertisement may include a relevant
advertisement for the same product, or may include a current
advertisement for an alternative product produced by the same product or
service provider.

[0067] The advertising module 215 may also be configured to log each
request for a current advertisement, and each successful presentation of
a current advertisement for proper apportionment of advertising revenue.
These events may be maintained within the system 200 as individual
records for each advertiser.

[0068] Advantageously, legacy advertisements accessed within the context
of a relational analysis may provide the basis for creating value from
legacy advertisements that may no longer be relevant to the greater
public. For example, an individual who views a legacy video advertisement
for a product based upon the fact that the legacy advertisement includes
a favorite musician, may now be provided with a current advertisement
from the same product provider for the same or even a different product.
While this legacy advertisement may no longer be relevant to the greater
public, the individual's interest in the musician serves as a basis for
extending the life of the legacy advertisement.

[0069] Dynamically Rotating Advertising Content

[0070] In some applications, the system 200 may utilize a rotating
advertisement schema or campaign that substantially reduces advertisement
fatigue. For example, the system 200 may utilize a central advertising
theme that includes the promotion of a movie. Rather than presenting a
video trailer for the movie each time a targeted customer visits a
website, the system 200 may obtain a plurality of advertisements
associated with the promotion of the movie, such as interviews with the
actors, soundtrack advertisements, posters, and the like. Utilizing the
plurality of advertisements, the system 200 may establish a central
advertising object that is presented for a predetermined amount of time.
One or more of the additional or supporting advertisements may be
disposed proximately around the central advertising object.

[0071] Over time the system 200 may replace the central advertising object
with one of the additional advertising objects and move the central
advertising object to a supporting position. The system 200 may
selectively replace the central advertising object according to a
predetermine schedule, or may configure to replace the central
advertising object based upon web analytics such as repeated page views
from the same Internet protocol address within a given period of time.

[0072]FIG. 3 is a flowchart of an exemplary method 300 for providing
current advertisements based upon the provision of a legacy
advertisement. The method may include the step 305 of receiving data
(e.g., a signal) that a legacy advertisement has been requested. This
request may include an individual clicking or otherwise accessing the
legacy advertisement. The accessing of the legacy advertisement may
generate a signal that is provided to the analysis module of the
relational marketing system. According to some embodiments, the signal
may include descriptive data such as the creation date, original run date
(when the advertisement was utilized), subject matter, metadata, tags,
and so forth.

[0073] Upon receiving a signal, the method may include the step 310 of
evaluating the descriptive data to determine one or more objects included
in the signal. Objects may include any of names, locations, dates, and
events--just to name a few.

[0074] Next, the method may include a step 315 of locating a current
advertisement that corresponds to the legacy advertisement. This step 315
may include querying local or remote (e.g., third party) databases
utilizing the evaluated data included in the signal to locate one or more
current advertisements.

[0075] If two or more current advertisements are located, the method 300
may also include a step 320 of selecting which of the located current
advertisements should be displayed. The selection of advertisements may
be based upon relevance or preferences of the individual (may be based
upon web analytics), or may be based upon the subject matter of the
legacy advertisement.

[0076] Finally, the method may include a step 325 of providing one or more
of the selected current advertisements. This step may include publishing
the advertisements to a web based interface or providing the
advertisements via an application or direct communication utilizing
various communication protocols such as short message system ("SMS"),
electronic mail, and so forth.

[0077]FIG. 4A is a flowchart of an exemplary method 400 for providing
selective advertisements based upon relational data. The method 400 may
begin with a step 405 of receiving a query that includes information
indicative of one or more objects. Responsive to receiving the query, the
method 410 may include the step 410 of evaluating the query to determine
one or more objects included therein.

[0078] In some embodiments, the method may also include a step of
receiving a plurality of responses to question provided to the
individual, rather than (or in addition to) utilizing only information
gathered from the query. In this way, additional preference data may be
obtained to enhance the selection of appropriate suggestive advertising.

[0079] Upon determining one or more objects, the method may include the
step 415 of searching a database for additional objects connected to the
one or more objects. It will be understood that the connections between
these additional objects and the one or more objects of the query may be
previously determined via relational analyses.

[0080] Assuming one or more additional objects were located by searching
the database, the method may include the step 420 of weighting or ranking
the located objects based upon any of a number of factors such as
connection number, connection type, and the like.

[0081] Next, the method may include providing suggestive advertisements
for products or services associated with the located objects in step 425,
in response to receiving a query. Therefore, the selection of suggestive
advertisements may be based upon indirect information that ties the
objects of the query to one or more additional objects. For example, the
system may provide suggestive advertisements for donations to nonprofit
organizations based upon information such as celebrity endorsements.
Because the individual has an expressed interested in numerous
celebrities that have endorsed the same nonprofit agency, a suggestive
advertisement for donating to a particular nonprofit agency may be
presented.

[0082] FIG. 4B a flowchart of another exemplary method 430 for providing
selective advertisements based upon relational data. The method may
comprise a step 435 of receiving query via a web server, from a client
device. The method may also include a step 440 of generating, via the web
server, a response for the query by executing a sub-step 445 of
determining a header object in the query. The step 440 may also comprise
a sub-step 450 of determining connected entities in a database for the
header object, along with a sub-step 455 of assembling the connected
entities together into the response according to a long-tail response
format. Additionally, the method may comprise a step 460 of returning the
response to the client device.

[0083]FIG. 5 illustrates an exemplary computing system 500 that may be
used to implement an embodiment of the present technology. The computing
system 500 of FIG. 5 includes one or more processors 510 and main memory
520. Main memory 520 stores, in part, instructions and data for execution
by processor 510. Main memory 520 can store the executable code when the
system 500 is in operation. The system 500 of FIG. 5 may further include
a mass storage device 530, portable storage devices 540, output devices
550, user input devices 560, a graphics display 570, and other peripheral
devices 580.

[0084] The components shown in FIG. 5 are depicted as being connected via
a single bus 590. The components may be connected through one or more
data transport means. Processor unit 510 and main memory 520 may be
connected via a local microprocessor bus, and the mass storage device
530, peripheral device(s) 580, portable storage device(s) 540, and
graphics display system 570 may be connected via one or more input/output
(I/O) buses.

[0085] Mass storage device 530, which may be implemented with a magnetic
disk drive or an optical disk drive, is a non-volatile storage device for
storing data and instructions for use by processor unit 510. Mass storage
device 530 can store the system software for implementing embodiments of
the present technology for purposes of loading that software into main
memory 520.

[0086] Portable storage device 540 operates in conjunction with a portable
non-volatile storage media, such as a floppy disk, compact disk or
digital video disc, to input and output data and code to and from the
computer system 500 of FIG. 5. The system software for implementing
embodiments of the present technology may be stored on such a portable
media and input to the computer system 500 via the portable storage
device 540.

[0087] User input devices 560 provide a portion of a user interface. User
input devices 560 may include an alphanumeric keypad, such as a keyboard,
for inputting alphanumeric and other data, or a pointing device, such as
a mouse, a trackball, stylus, or cursor direction keys. Additionally, the
system 500 as shown in FIG. 5 includes output devices 550. Suitable
output devices include speakers, printers, network interfaces, and
monitors.

[0088] Graphics display system 570 may include a liquid crystal display
(LCD) or other suitable display device. Graphics display system 570
receives textual and graphical data, and processes the data for output to
the display device.

[0089] Peripheral devices 580 may include any type of computer support
device to add additional functionality to the computer system. Peripheral
device(s) 580 may include a modem or a router.

[0090] The components contained in the computer system 500 of FIG. 5 are
those typically found in computer systems that may be suitable for use
with embodiments of the present technology and are intended to represent
a broad category of such computer components that are well known in the
art. Thus, the computer system 500 of FIG. 5 can be a personal computer,
hand held computing system, telephone, mobile computing system,
workstation, server, minicomputer, mainframe computer, or any other
computing system. The computer can also include different bus
configurations, networked platforms, multi-processor platforms, etc.
Various operating systems can be used including UNIX, Linux, Windows,
Macintosh OS, Palm OS, and other suitable operating systems.

[0091] Some of the above-described functions may be composed of
instructions that are stored on storage media (e.g., computer-readable
media). The instructions may be retrieved and executed by the processor.
Some examples of storage media are memory devices, tapes, disks, and the
like. The instructions are operational when executed by the processor to
direct the processor to operate in accord with the technology. Those
skilled in the art are familiar with instructions, processor(s), and
storage media.

[0092] It is noteworthy that any hardware platform suitable for performing
the processing described herein is suitable for use with the technology.
The terms "computer-readable storage media" and "computer-readable
storage media" as used herein refer to any media or media that
participate in providing instructions to a CPU for execution. Such media
can take many forms, including, but not limited to, non-volatile media,
volatile media and transmission media. Non-volatile media include, for
example, optical or magnetic disks, such as a fixed disk. Volatile media
include dynamic memory, such as system RAM. Transmission media include
coaxial cables, copper wire and fiber optics, among others, including the
wires that comprise one embodiment of a bus. Transmission media can also
take the form of acoustic or light waves, such as those generated during
radio frequency (RF) and infrared (IR) data communications. Common forms
of computer-readable media include, for example, a floppy disk, a
flexible disk, a hard disk, magnetic tape, any other magnetic media, a
CD-ROM disk, digital video disk (DVD), any other optical media, any other
physical media with patterns of marks or holes, a RAM, a PROM, an EPROM,
an EEPROM, a FLASHEPROM, any other memory chip or data exchange adapter,
a carrier wave, or any other media from which a computer can read.

[0093] Various forms of computer-readable media may be involved in
carrying one or more sequences of one or more instructions to a CPU for
execution. A bus carries the data to system RAM, from which a CPU
retrieves and executes the instructions. The instructions received by
system RAM can optionally be stored on a fixed disk either before or
after execution by a CPU.

[0094] The above description is illustrative and not restrictive. Many
variations of the technology will become apparent to those of skill in
the art upon review of this disclosure. The scope of the technology
should, therefore, be determined not with reference to the above
description.